Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is a growing interest in increasing walking in urban areas, partly to reduce pollution and other problems related to transportation by cars, and partly to improve public health (through reasonable exercise such as walking). In this study several factors that influence the amount of pedestrian movement in Tehran (Iran) are explored. Data were collected through questionnaires and interviews, and included sociodemographic indicators, people's perceptions of the neighborhoods where they live or work, and daily walking time in District 6 of the City of Tehran. The results of the study show that security, street connectivity, public health education, and sociodemographic indicators such as age and education influence pedestrian movement in residential areas. Local sociocultural behavior and indicators such as age and education were found to be the most influential in the commercial areas in the study. On the other hand, the respondents' behavior showed that there is a surprisingly low tendency in the City of Tehran to walk out of choice. Almost all pedestrian movement appears to be in response to a need or an obligation to walk, such as for business or essential shopping.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it